1. Field of the Invention
This invention relates to interpolation.
2. Description of the Prior Art
Pixel interpolation techniques have been proposed, for use in image or video processing systems, in which the interpolation of output pixels from input pixels depends on the detected directions of image features around the input pixels. It has been proposed that the detection of the direction or angle of such image features can be carried out by finding a direction of lowest variance amongst the input pixels.
The angle detection process can be conducted (for example) on a greyscale (monochromatic) version of the input pixels or separately on each GBR (green, blue, red) component of the input pixels. If the latter is used, then the GBR results can be combined (e.g. according to the standard ratios of G, B and R used in the generation of a luminance (Y) value) so as to generate a single output result. It is desirable to operate on monochromatic pixels to save on processing or hardware requirements.
A problem can arise in areas of low image detail. In order to avoid finding incorrect angles in areas of low picture detail, the image activity of pixels around a current pixel position under test can be detected, and the degree of confidence associated with a detected angle can be varied in dependence on the image activity level. This degree of confidence can then be used to change the interpolation method used at that position. This arrangement is to avoid using angles detected merely because of minor variations in an otherwise non-detailed area of the image. Image activity can be measured in various ways, for example by detecting pixel variance, standard deviation, differences and the like.
As mentioned above, a benefit of converting the input pixels to greyscale for the purposes of angle detection is that the angle finding process needs be conducted on only one colour channel rather than on three separate channels. There can therefore be a potential reduction in hardware or processing requirements. For example, colour component (GBR) data could be converted to greyscale (Y) using the following formula:Y=g Coeff*G+b Coeff*B+r Coeff*R 
where, gCoeff and bCoeff, rCoeff may be the standard colour conversion coefficients (that is, the coefficients used to generate a standard Y value from G, B and R values, one example being Y=0.2126 R+0.7152 G+0.0722 B). However, using fixed coefficients in this way, two very different colours in the GBR colour space could produce identical greyscale colours, and therefore a particular image feature might not be detected in the resulting greyscale image.
It is an object of the invention to provide an improved pixel interpolation technique.